1. Field of the Invention
The invention generally relates to noise suppression.
2. Background
Speech recognition (a.k.a. automatic speech recognition) techniques use a person's speech to perform operations such as composing a document, dialing a telephone number, controlling a processing system (e.g., a computer), etc. The person's speech typically is sampled to provide speech samples. The speech samples are compared to reference samples to determine the content of the speech (i.e., what the person is saying). For example, each reference sample may represent a word or a phoneme. By identifying the words or phonemes that correspond to the speech samples, the content of the speech may be determined.
Each of the speech samples and the reference samples commonly has a speech component and a noise component. The speech component represents the person's speech. The noise component represents sounds other than the person's speech (e.g., background noise). It may be desirable to suppress the effect of the noise components (referred to herein as “noise”) to more effectively match the speech samples to the reference samples.
However, conventional techniques for suppressing noise in speech samples and reference samples often are computationally complex, which may render such techniques infeasible for resource-constrained applications. For example, front end spectral enhancement techniques traditionally are built upon statistical or subspace approaches, which may be computationally intensive. Moreover, noise robust processing traditionally is performed in the linear frequency domain. Such processing becomes relatively complex when spectral analysis is performed at relatively high resolutions.